/* * Copyright 2011-2013 Blender Foundation * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License */ #include #include #include #include "device.h" #include "device_intern.h" #include "buffers.h" #include "util_cuda.h" #include "util_debug.h" #include "util_map.h" #include "util_opengl.h" #include "util_path.h" #include "util_system.h" #include "util_types.h" #include "util_time.h" CCL_NAMESPACE_BEGIN class CUDADevice : public Device { public: DedicatedTaskPool task_pool; CUdevice cuDevice; CUcontext cuContext; CUmodule cuModule; map tex_interp_map; int cuDevId; int cuDevArchitecture; bool first_error; bool use_texture_storage; struct PixelMem { GLuint cuPBO; CUgraphicsResource cuPBOresource; GLuint cuTexId; int w, h; }; map pixel_mem_map; CUdeviceptr cuda_device_ptr(device_ptr mem) { return (CUdeviceptr)mem; } static const char *cuda_error_string(CUresult result) { switch(result) { case CUDA_SUCCESS: return "No errors"; case CUDA_ERROR_INVALID_VALUE: return "Invalid value"; case CUDA_ERROR_OUT_OF_MEMORY: return "Out of memory"; case CUDA_ERROR_NOT_INITIALIZED: return "Driver not initialized"; case CUDA_ERROR_DEINITIALIZED: return "Driver deinitialized"; case CUDA_ERROR_NO_DEVICE: return "No CUDA-capable device available"; case CUDA_ERROR_INVALID_DEVICE: return "Invalid device"; case CUDA_ERROR_INVALID_IMAGE: return "Invalid kernel image"; case CUDA_ERROR_INVALID_CONTEXT: return "Invalid context"; case CUDA_ERROR_CONTEXT_ALREADY_CURRENT: return "Context already current"; case CUDA_ERROR_MAP_FAILED: return "Map failed"; case CUDA_ERROR_UNMAP_FAILED: return "Unmap failed"; case CUDA_ERROR_ARRAY_IS_MAPPED: return "Array is mapped"; case CUDA_ERROR_ALREADY_MAPPED: return "Already mapped"; case CUDA_ERROR_NO_BINARY_FOR_GPU: return "No binary for GPU"; case CUDA_ERROR_ALREADY_ACQUIRED: return "Already acquired"; case CUDA_ERROR_NOT_MAPPED: return "Not mapped"; case CUDA_ERROR_NOT_MAPPED_AS_ARRAY: return "Mapped resource not available for access as an array"; case CUDA_ERROR_NOT_MAPPED_AS_POINTER: return "Mapped resource not available for access as a pointer"; case CUDA_ERROR_ECC_UNCORRECTABLE: return "Uncorrectable ECC error detected"; case CUDA_ERROR_UNSUPPORTED_LIMIT: return "CUlimit not supported by device"; case CUDA_ERROR_INVALID_SOURCE: return "Invalid source"; case CUDA_ERROR_FILE_NOT_FOUND: return "File not found"; case CUDA_ERROR_SHARED_OBJECT_SYMBOL_NOT_FOUND: return "Link to a shared object failed to resolve"; case CUDA_ERROR_SHARED_OBJECT_INIT_FAILED: return "Shared object initialization failed"; case CUDA_ERROR_INVALID_HANDLE: return "Invalid handle"; case CUDA_ERROR_NOT_FOUND: return "Not found"; case CUDA_ERROR_NOT_READY: return "CUDA not ready"; case CUDA_ERROR_LAUNCH_FAILED: return "Launch failed"; case CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES: return "Launch exceeded resources"; case CUDA_ERROR_LAUNCH_TIMEOUT: return "Launch exceeded timeout"; case CUDA_ERROR_LAUNCH_INCOMPATIBLE_TEXTURING: return "Launch with incompatible texturing"; case CUDA_ERROR_UNKNOWN: return "Unknown error"; default: return "Unknown CUDA error value"; } } /*#ifdef NDEBUG #define cuda_abort() #else #define cuda_abort() abort() #endif*/ void cuda_error_documentation() { if(first_error) { fprintf(stderr, "\nRefer to the Cycles GPU rendering documentation for possible solutions:\n"); fprintf(stderr, "http://wiki.blender.org/index.php/Doc:2.6/Manual/Render/Cycles/GPU_Rendering\n\n"); first_error = false; } } #define cuda_assert(stmt) \ { \ CUresult result = stmt; \ \ if(result != CUDA_SUCCESS) { \ string message = string_printf("CUDA error: %s in %s", cuda_error_string(result), #stmt); \ if(error_msg == "") \ error_msg = message; \ fprintf(stderr, "%s\n", message.c_str()); \ /*cuda_abort();*/ \ cuda_error_documentation(); \ } \ } bool cuda_error_(CUresult result, const string& stmt) { if(result == CUDA_SUCCESS) return false; string message = string_printf("CUDA error at %s: %s", stmt.c_str(), cuda_error_string(result)); if(error_msg == "") error_msg = message; fprintf(stderr, "%s\n", message.c_str()); cuda_error_documentation(); return true; } #define cuda_error(stmt) cuda_error_(stmt, #stmt) void cuda_error_message(const string& message) { if(error_msg == "") error_msg = message; fprintf(stderr, "%s\n", message.c_str()); cuda_error_documentation(); } void cuda_push_context() { cuda_assert(cuCtxSetCurrent(cuContext)) } void cuda_pop_context() { cuda_assert(cuCtxSetCurrent(NULL)); } CUDADevice(DeviceInfo& info, Stats &stats, bool background_) : Device(stats) { first_error = true; background = background_; use_texture_storage = true; cuDevId = info.num; cuDevice = 0; cuContext = 0; /* intialize */ if(cuda_error(cuInit(0))) return; /* setup device and context */ if(cuda_error(cuDeviceGet(&cuDevice, cuDevId))) return; CUresult result; if(background) { result = cuCtxCreate(&cuContext, 0, cuDevice); } else { result = cuGLCtxCreate(&cuContext, 0, cuDevice); if(result != CUDA_SUCCESS) { result = cuCtxCreate(&cuContext, 0, cuDevice); background = true; } } if(cuda_error_(result, "cuCtxCreate")) return; int major, minor; cuDeviceComputeCapability(&major, &minor, cuDevId); cuDevArchitecture = major*100 + minor*10; /* In order to use full 6GB of memory on Titan cards, use arrays instead * of textures. On earlier cards this seems slower, but on Titan it is * actually slightly faster in tests. */ use_texture_storage = (cuDevArchitecture < 350); cuda_pop_context(); } ~CUDADevice() { task_pool.stop(); cuda_assert(cuCtxDestroy(cuContext)) } bool support_device(bool experimental) { int major, minor; cuDeviceComputeCapability(&major, &minor, cuDevId); if(major < 2) { cuda_error_message(string_printf("CUDA device supported only with compute capability 2.0 or up, found %d.%d.", major, minor)); return false; } return true; } string compile_kernel() { /* compute cubin name */ int major, minor; cuDeviceComputeCapability(&major, &minor, cuDevId); /* attempt to use kernel provided with blender */ string cubin = path_get(string_printf("lib/kernel_sm_%d%d.cubin", major, minor)); if(path_exists(cubin)) return cubin; /* not found, try to use locally compiled kernel */ string kernel_path = path_get("kernel"); string md5 = path_files_md5_hash(kernel_path); cubin = string_printf("cycles_kernel_sm%d%d_%s.cubin", major, minor, md5.c_str()); cubin = path_user_get(path_join("cache", cubin)); /* if exists already, use it */ if(path_exists(cubin)) return cubin; #ifdef _WIN32 if(cuHavePrecompiledKernels()) { if(major < 2) cuda_error_message(string_printf("CUDA device requires compute capability 2.0 or up, found %d.%d. Your GPU is not supported.", major, minor)); else cuda_error_message(string_printf("CUDA binary kernel for this graphics card compute capability (%d.%d) not found.", major, minor)); return ""; } #endif /* if not, find CUDA compiler */ string nvcc = cuCompilerPath(); if(nvcc == "") { cuda_error_message("CUDA nvcc compiler not found. Install CUDA toolkit in default location."); return ""; } int cuda_version = cuCompilerVersion(); if(cuda_version == 0) { cuda_error_message("CUDA nvcc compiler version could not be parsed."); return ""; } if(cuda_version < 50) { printf("Unsupported CUDA version %d.%d detected, you need CUDA 5.0.\n", cuda_version/10, cuda_version%10); return ""; } else if(cuda_version > 50) printf("CUDA version %d.%d detected, build may succeed but only CUDA 5.0 is officially supported.\n", cuda_version/10, cuda_version%10); /* compile */ string kernel = path_join(kernel_path, "kernel.cu"); string include = kernel_path; const int machine = system_cpu_bits(); string arch_flags; /* CUDA 5.x build flags for different archs */ if(major == 2) { /* sm_2x */ arch_flags = "--maxrregcount=32 --use_fast_math"; } else if(major == 3) { /* sm_3x */ arch_flags = "--maxrregcount=32 --use_fast_math"; } double starttime = time_dt(); printf("Compiling CUDA kernel ...\n"); path_create_directories(cubin); string command = string_printf("\"%s\" -arch=sm_%d%d -m%d --cubin \"%s\" " "-o \"%s\" --ptxas-options=\"-v\" %s -I\"%s\" -DNVCC -D__KERNEL_CUDA_VERSION__=%d", nvcc.c_str(), major, minor, machine, kernel.c_str(), cubin.c_str(), arch_flags.c_str(), include.c_str(), cuda_version); printf("%s\n", command.c_str()); if(system(command.c_str()) == -1) { cuda_error_message("Failed to execute compilation command, see console for details."); return ""; } /* verify if compilation succeeded */ if(!path_exists(cubin)) { cuda_error_message("CUDA kernel compilation failed, see console for details."); return ""; } printf("Kernel compilation finished in %.2lfs.\n", time_dt() - starttime); return cubin; } bool load_kernels(bool experimental) { /* check if cuda init succeeded */ if(cuContext == 0) return false; /* check if GPU is supported with current feature set */ if(!support_device(experimental)) return false; /* get kernel */ string cubin = compile_kernel(); if(cubin == "") return false; /* open module */ cuda_push_context(); CUresult result = cuModuleLoad(&cuModule, cubin.c_str()); if(cuda_error_(result, "cuModuleLoad")) cuda_error_message(string_printf("Failed loading CUDA kernel %s.", cubin.c_str())); cuda_pop_context(); return (result == CUDA_SUCCESS); } void mem_alloc(device_memory& mem, MemoryType type) { cuda_push_context(); CUdeviceptr device_pointer; size_t size = mem.memory_size(); cuda_assert(cuMemAlloc(&device_pointer, size)) mem.device_pointer = (device_ptr)device_pointer; stats.mem_alloc(size); cuda_pop_context(); } void mem_copy_to(device_memory& mem) { cuda_push_context(); if(mem.device_pointer) cuda_assert(cuMemcpyHtoD(cuda_device_ptr(mem.device_pointer), (void*)mem.data_pointer, mem.memory_size())) cuda_pop_context(); } void mem_copy_from(device_memory& mem, int y, int w, int h, int elem) { size_t offset = elem*y*w; size_t size = elem*w*h; cuda_push_context(); if(mem.device_pointer) { cuda_assert(cuMemcpyDtoH((uchar*)mem.data_pointer + offset, (CUdeviceptr)((uchar*)mem.device_pointer + offset), size)) } else { memset((char*)mem.data_pointer + offset, 0, size); } cuda_pop_context(); } void mem_zero(device_memory& mem) { memset((void*)mem.data_pointer, 0, mem.memory_size()); cuda_push_context(); if(mem.device_pointer) cuda_assert(cuMemsetD8(cuda_device_ptr(mem.device_pointer), 0, mem.memory_size())) cuda_pop_context(); } void mem_free(device_memory& mem) { if(mem.device_pointer) { cuda_push_context(); cuda_assert(cuMemFree(cuda_device_ptr(mem.device_pointer))) cuda_pop_context(); mem.device_pointer = 0; stats.mem_free(mem.memory_size()); } } void const_copy_to(const char *name, void *host, size_t size) { CUdeviceptr mem; size_t bytes; cuda_push_context(); cuda_assert(cuModuleGetGlobal(&mem, &bytes, cuModule, name)) //assert(bytes == size); cuda_assert(cuMemcpyHtoD(mem, host, size)) cuda_pop_context(); } void tex_alloc(const char *name, device_memory& mem, bool interpolation, bool periodic) { /* determine format */ CUarray_format_enum format; size_t dsize = datatype_size(mem.data_type); size_t size = mem.memory_size(); bool use_texture = interpolation || use_texture_storage; if(use_texture) { switch(mem.data_type) { case TYPE_UCHAR: format = CU_AD_FORMAT_UNSIGNED_INT8; break; case TYPE_UINT: format = CU_AD_FORMAT_UNSIGNED_INT32; break; case TYPE_INT: format = CU_AD_FORMAT_SIGNED_INT32; break; case TYPE_FLOAT: format = CU_AD_FORMAT_FLOAT; break; default: assert(0); return; } CUtexref texref = NULL; cuda_push_context(); cuda_assert(cuModuleGetTexRef(&texref, cuModule, name)) if(!texref) { cuda_pop_context(); return; } if(interpolation) { CUarray handle = NULL; CUDA_ARRAY_DESCRIPTOR desc; desc.Width = mem.data_width; desc.Height = mem.data_height; desc.Format = format; desc.NumChannels = mem.data_elements; cuda_assert(cuArrayCreate(&handle, &desc)) if(!handle) { cuda_pop_context(); return; } if(mem.data_height > 1) { CUDA_MEMCPY2D param; memset(¶m, 0, sizeof(param)); param.dstMemoryType = CU_MEMORYTYPE_ARRAY; param.dstArray = handle; param.srcMemoryType = CU_MEMORYTYPE_HOST; param.srcHost = (void*)mem.data_pointer; param.srcPitch = mem.data_width*dsize*mem.data_elements; param.WidthInBytes = param.srcPitch; param.Height = mem.data_height; cuda_assert(cuMemcpy2D(¶m)) } else cuda_assert(cuMemcpyHtoA(handle, 0, (void*)mem.data_pointer, size)) cuda_assert(cuTexRefSetArray(texref, handle, CU_TRSA_OVERRIDE_FORMAT)) cuda_assert(cuTexRefSetFilterMode(texref, CU_TR_FILTER_MODE_LINEAR)) cuda_assert(cuTexRefSetFlags(texref, CU_TRSF_NORMALIZED_COORDINATES)) mem.device_pointer = (device_ptr)handle; stats.mem_alloc(size); } else { cuda_pop_context(); mem_alloc(mem, MEM_READ_ONLY); mem_copy_to(mem); cuda_push_context(); cuda_assert(cuTexRefSetAddress(NULL, texref, cuda_device_ptr(mem.device_pointer), size)) cuda_assert(cuTexRefSetFilterMode(texref, CU_TR_FILTER_MODE_POINT)) cuda_assert(cuTexRefSetFlags(texref, CU_TRSF_READ_AS_INTEGER)) } if(periodic) { cuda_assert(cuTexRefSetAddressMode(texref, 0, CU_TR_ADDRESS_MODE_WRAP)) cuda_assert(cuTexRefSetAddressMode(texref, 1, CU_TR_ADDRESS_MODE_WRAP)) } else { cuda_assert(cuTexRefSetAddressMode(texref, 0, CU_TR_ADDRESS_MODE_CLAMP)) cuda_assert(cuTexRefSetAddressMode(texref, 1, CU_TR_ADDRESS_MODE_CLAMP)) } cuda_assert(cuTexRefSetFormat(texref, format, mem.data_elements)) cuda_pop_context(); } else { mem_alloc(mem, MEM_READ_ONLY); mem_copy_to(mem); cuda_push_context(); CUdeviceptr cumem; size_t cubytes; cuda_assert(cuModuleGetGlobal(&cumem, &cubytes, cuModule, name)) if(cubytes == 8) { /* 64 bit device pointer */ uint64_t ptr = mem.device_pointer; cuda_assert(cuMemcpyHtoD(cumem, (void*)&ptr, cubytes)) } else { /* 32 bit device pointer */ uint32_t ptr = (uint32_t)mem.device_pointer; cuda_assert(cuMemcpyHtoD(cumem, (void*)&ptr, cubytes)) } cuda_pop_context(); } tex_interp_map[mem.device_pointer] = interpolation; } void tex_free(device_memory& mem) { if(mem.device_pointer) { if(tex_interp_map[mem.device_pointer]) { cuda_push_context(); cuArrayDestroy((CUarray)mem.device_pointer); cuda_pop_context(); tex_interp_map.erase(tex_interp_map.find(mem.device_pointer)); mem.device_pointer = 0; stats.mem_free(mem.memory_size()); } else { tex_interp_map.erase(tex_interp_map.find(mem.device_pointer)); mem_free(mem); } } } void path_trace(RenderTile& rtile, int sample, bool branched) { if(have_error()) return; cuda_push_context(); CUfunction cuPathTrace; CUdeviceptr d_buffer = cuda_device_ptr(rtile.buffer); CUdeviceptr d_rng_state = cuda_device_ptr(rtile.rng_state); /* get kernel function */ if(branched) cuda_assert(cuModuleGetFunction(&cuPathTrace, cuModule, "kernel_cuda_branched_path_trace")) else cuda_assert(cuModuleGetFunction(&cuPathTrace, cuModule, "kernel_cuda_path_trace")) if(have_error()) return; /* pass in parameters */ int offset = 0; cuda_assert(cuParamSetv(cuPathTrace, offset, &d_buffer, sizeof(d_buffer))) offset += sizeof(d_buffer); cuda_assert(cuParamSetv(cuPathTrace, offset, &d_rng_state, sizeof(d_rng_state))) offset += sizeof(d_rng_state); offset = align_up(offset, __alignof(sample)); cuda_assert(cuParamSeti(cuPathTrace, offset, sample)) offset += sizeof(sample); cuda_assert(cuParamSeti(cuPathTrace, offset, rtile.x)) offset += sizeof(rtile.x); cuda_assert(cuParamSeti(cuPathTrace, offset, rtile.y)) offset += sizeof(rtile.y); cuda_assert(cuParamSeti(cuPathTrace, offset, rtile.w)) offset += sizeof(rtile.w); cuda_assert(cuParamSeti(cuPathTrace, offset, rtile.h)) offset += sizeof(rtile.h); cuda_assert(cuParamSeti(cuPathTrace, offset, rtile.offset)) offset += sizeof(rtile.offset); cuda_assert(cuParamSeti(cuPathTrace, offset, rtile.stride)) offset += sizeof(rtile.stride); cuda_assert(cuParamSetSize(cuPathTrace, offset)) /* launch kernel: todo find optimal size, cache config for fermi */ int xthreads = 16; int ythreads = 16; int xblocks = (rtile.w + xthreads - 1)/xthreads; int yblocks = (rtile.h + ythreads - 1)/ythreads; cuda_assert(cuFuncSetCacheConfig(cuPathTrace, CU_FUNC_CACHE_PREFER_L1)) cuda_assert(cuFuncSetBlockShape(cuPathTrace, xthreads, ythreads, 1)) cuda_assert(cuLaunchGrid(cuPathTrace, xblocks, yblocks)) cuda_assert(cuCtxSynchronize()) cuda_pop_context(); } void film_convert(DeviceTask& task, device_ptr buffer, device_ptr rgba_byte, device_ptr rgba_half) { if(have_error()) return; cuda_push_context(); CUfunction cuFilmConvert; CUdeviceptr d_rgba = map_pixels((rgba_byte)? rgba_byte: rgba_half); CUdeviceptr d_buffer = cuda_device_ptr(buffer); /* get kernel function */ if(rgba_half) cuda_assert(cuModuleGetFunction(&cuFilmConvert, cuModule, "kernel_cuda_convert_to_half_float")) else cuda_assert(cuModuleGetFunction(&cuFilmConvert, cuModule, "kernel_cuda_convert_to_byte")) /* pass in parameters */ int offset = 0; cuda_assert(cuParamSetv(cuFilmConvert, offset, &d_rgba, sizeof(d_rgba))) offset += sizeof(d_rgba); cuda_assert(cuParamSetv(cuFilmConvert, offset, &d_buffer, sizeof(d_buffer))) offset += sizeof(d_buffer); float sample_scale = 1.0f/(task.sample + 1); offset = align_up(offset, __alignof(sample_scale)); cuda_assert(cuParamSetf(cuFilmConvert, offset, sample_scale)) offset += sizeof(sample_scale); cuda_assert(cuParamSeti(cuFilmConvert, offset, task.x)) offset += sizeof(task.x); cuda_assert(cuParamSeti(cuFilmConvert, offset, task.y)) offset += sizeof(task.y); cuda_assert(cuParamSeti(cuFilmConvert, offset, task.w)) offset += sizeof(task.w); cuda_assert(cuParamSeti(cuFilmConvert, offset, task.h)) offset += sizeof(task.h); cuda_assert(cuParamSeti(cuFilmConvert, offset, task.offset)) offset += sizeof(task.offset); cuda_assert(cuParamSeti(cuFilmConvert, offset, task.stride)) offset += sizeof(task.stride); cuda_assert(cuParamSetSize(cuFilmConvert, offset)) /* launch kernel: todo find optimal size, cache config for fermi */ int xthreads = 16; int ythreads = 16; int xblocks = (task.w + xthreads - 1)/xthreads; int yblocks = (task.h + ythreads - 1)/ythreads; cuda_assert(cuFuncSetCacheConfig(cuFilmConvert, CU_FUNC_CACHE_PREFER_L1)) cuda_assert(cuFuncSetBlockShape(cuFilmConvert, xthreads, ythreads, 1)) cuda_assert(cuLaunchGrid(cuFilmConvert, xblocks, yblocks)) unmap_pixels((rgba_byte)? rgba_byte: rgba_half); cuda_pop_context(); } void shader(DeviceTask& task) { if(have_error()) return; cuda_push_context(); CUfunction cuDisplace; CUdeviceptr d_input = cuda_device_ptr(task.shader_input); CUdeviceptr d_output = cuda_device_ptr(task.shader_output); /* get kernel function */ cuda_assert(cuModuleGetFunction(&cuDisplace, cuModule, "kernel_cuda_shader")) /* pass in parameters */ int offset = 0; cuda_assert(cuParamSetv(cuDisplace, offset, &d_input, sizeof(d_input))) offset += sizeof(d_input); cuda_assert(cuParamSetv(cuDisplace, offset, &d_output, sizeof(d_output))) offset += sizeof(d_output); int shader_eval_type = task.shader_eval_type; offset = align_up(offset, __alignof(shader_eval_type)); cuda_assert(cuParamSeti(cuDisplace, offset, task.shader_eval_type)) offset += sizeof(task.shader_eval_type); cuda_assert(cuParamSeti(cuDisplace, offset, task.shader_x)) offset += sizeof(task.shader_x); cuda_assert(cuParamSetSize(cuDisplace, offset)) /* launch kernel: todo find optimal size, cache config for fermi */ int xthreads = 16; int xblocks = (task.shader_w + xthreads - 1)/xthreads; cuda_assert(cuFuncSetCacheConfig(cuDisplace, CU_FUNC_CACHE_PREFER_L1)) cuda_assert(cuFuncSetBlockShape(cuDisplace, xthreads, 1, 1)) cuda_assert(cuLaunchGrid(cuDisplace, xblocks, 1)) cuda_pop_context(); } CUdeviceptr map_pixels(device_ptr mem) { if(!background) { PixelMem pmem = pixel_mem_map[mem]; CUdeviceptr buffer; size_t bytes; cuda_assert(cuGraphicsMapResources(1, &pmem.cuPBOresource, 0)) cuda_assert(cuGraphicsResourceGetMappedPointer(&buffer, &bytes, pmem.cuPBOresource)) return buffer; } return cuda_device_ptr(mem); } void unmap_pixels(device_ptr mem) { if(!background) { PixelMem pmem = pixel_mem_map[mem]; cuda_assert(cuGraphicsUnmapResources(1, &pmem.cuPBOresource, 0)) } } void pixels_alloc(device_memory& mem) { if(!background) { PixelMem pmem; pmem.w = mem.data_width; pmem.h = mem.data_height; cuda_push_context(); glGenBuffers(1, &pmem.cuPBO); glBindBuffer(GL_PIXEL_UNPACK_BUFFER, pmem.cuPBO); if(mem.data_type == TYPE_HALF) glBufferData(GL_PIXEL_UNPACK_BUFFER, pmem.w*pmem.h*sizeof(GLhalf)*4, NULL, GL_DYNAMIC_DRAW); else glBufferData(GL_PIXEL_UNPACK_BUFFER, pmem.w*pmem.h*sizeof(uint8_t)*4, NULL, GL_DYNAMIC_DRAW); glBindBuffer(GL_PIXEL_UNPACK_BUFFER, 0); glGenTextures(1, &pmem.cuTexId); glBindTexture(GL_TEXTURE_2D, pmem.cuTexId); if(mem.data_type == TYPE_HALF) glTexImage2D(GL_TEXTURE_2D, 0, GL_RGBA16F_ARB, pmem.w, pmem.h, 0, GL_RGBA, GL_HALF_FLOAT, NULL); else glTexImage2D(GL_TEXTURE_2D, 0, GL_RGBA, pmem.w, pmem.h, 0, GL_RGBA, GL_UNSIGNED_BYTE, NULL); glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_NEAREST); glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_NEAREST); glBindTexture(GL_TEXTURE_2D, 0); CUresult result = cuGraphicsGLRegisterBuffer(&pmem.cuPBOresource, pmem.cuPBO, CU_GRAPHICS_MAP_RESOURCE_FLAGS_NONE); if(result == CUDA_SUCCESS) { cuda_pop_context(); mem.device_pointer = pmem.cuTexId; pixel_mem_map[mem.device_pointer] = pmem; stats.mem_alloc(mem.memory_size()); return; } else { /* failed to register buffer, fallback to no interop */ glDeleteBuffers(1, &pmem.cuPBO); glDeleteTextures(1, &pmem.cuTexId); cuda_pop_context(); background = true; } } Device::pixels_alloc(mem); } void pixels_copy_from(device_memory& mem, int y, int w, int h) { if(!background) { PixelMem pmem = pixel_mem_map[mem.device_pointer]; cuda_push_context(); glBindBuffer(GL_PIXEL_UNPACK_BUFFER, pmem.cuPBO); uchar *pixels = (uchar*)glMapBuffer(GL_PIXEL_UNPACK_BUFFER, GL_READ_ONLY); size_t offset = sizeof(uchar)*4*y*w; memcpy((uchar*)mem.data_pointer + offset, pixels + offset, sizeof(uchar)*4*w*h); glUnmapBuffer(GL_PIXEL_UNPACK_BUFFER); glBindBuffer(GL_PIXEL_UNPACK_BUFFER, 0); cuda_pop_context(); return; } Device::pixels_copy_from(mem, y, w, h); } void pixels_free(device_memory& mem) { if(mem.device_pointer) { if(!background) { PixelMem pmem = pixel_mem_map[mem.device_pointer]; cuda_push_context(); cuda_assert(cuGraphicsUnregisterResource(pmem.cuPBOresource)) glDeleteBuffers(1, &pmem.cuPBO); glDeleteTextures(1, &pmem.cuTexId); cuda_pop_context(); pixel_mem_map.erase(pixel_mem_map.find(mem.device_pointer)); mem.device_pointer = 0; stats.mem_free(mem.memory_size()); return; } Device::pixels_free(mem); } } void draw_pixels(device_memory& mem, int y, int w, int h, int dy, int width, int height, bool transparent) { if(!background) { PixelMem pmem = pixel_mem_map[mem.device_pointer]; cuda_push_context(); /* for multi devices, this assumes the ineffecient method that we allocate * all pixels on the device even though we only render to a subset */ size_t offset = 4*y*w; if(mem.data_type == TYPE_HALF) offset *= sizeof(GLhalf); else offset *= sizeof(uint8_t); glBindBufferARB(GL_PIXEL_UNPACK_BUFFER_ARB, pmem.cuPBO); glBindTexture(GL_TEXTURE_2D, pmem.cuTexId); if(mem.data_type == TYPE_HALF) glTexSubImage2D(GL_TEXTURE_2D, 0, 0, 0, w, h, GL_RGBA, GL_HALF_FLOAT, (void*)offset); else glTexSubImage2D(GL_TEXTURE_2D, 0, 0, 0, w, h, GL_RGBA, GL_UNSIGNED_BYTE, (void*)offset); glBindBufferARB(GL_PIXEL_UNPACK_BUFFER_ARB, 0); glEnable(GL_TEXTURE_2D); if(transparent) { glEnable(GL_BLEND); glBlendFunc(GL_ONE, GL_ONE_MINUS_SRC_ALPHA); } glColor3f(1.0f, 1.0f, 1.0f); glPushMatrix(); glTranslatef(0.0f, (float)dy, 0.0f); glBegin(GL_QUADS); glTexCoord2f(0.0f, 0.0f); glVertex2f(0.0f, 0.0f); glTexCoord2f((float)w/(float)pmem.w, 0.0f); glVertex2f((float)width, 0.0f); glTexCoord2f((float)w/(float)pmem.w, (float)h/(float)pmem.h); glVertex2f((float)width, (float)height); glTexCoord2f(0.0f, (float)h/(float)pmem.h); glVertex2f(0.0f, (float)height); glEnd(); glPopMatrix(); if(transparent) glDisable(GL_BLEND); glBindTexture(GL_TEXTURE_2D, 0); glDisable(GL_TEXTURE_2D); cuda_pop_context(); return; } Device::draw_pixels(mem, y, w, h, dy, width, height, transparent); } void thread_run(DeviceTask *task) { if(task->type == DeviceTask::PATH_TRACE) { RenderTile tile; bool branched = task->integrator_branched; /* keep rendering tiles until done */ while(task->acquire_tile(this, tile)) { int start_sample = tile.start_sample; int end_sample = tile.start_sample + tile.num_samples; for(int sample = start_sample; sample < end_sample; sample++) { if (task->get_cancel()) { if(task->need_finish_queue == false) break; } path_trace(tile, sample, branched); tile.sample = sample + 1; task->update_progress(tile); } task->release_tile(tile); } } else if(task->type == DeviceTask::SHADER) { shader(*task); cuda_push_context(); cuda_assert(cuCtxSynchronize()) cuda_pop_context(); } } class CUDADeviceTask : public DeviceTask { public: CUDADeviceTask(CUDADevice *device, DeviceTask& task) : DeviceTask(task) { run = function_bind(&CUDADevice::thread_run, device, this); } }; void task_add(DeviceTask& task) { if(task.type == DeviceTask::FILM_CONVERT) { /* must be done in main thread due to opengl access */ film_convert(task, task.buffer, task.rgba_byte, task.rgba_half); cuda_push_context(); cuda_assert(cuCtxSynchronize()) cuda_pop_context(); } else { task_pool.push(new CUDADeviceTask(this, task)); } } void task_wait() { task_pool.wait(); } void task_cancel() { task_pool.cancel(); } }; Device *device_cuda_create(DeviceInfo& info, Stats &stats, bool background) { return new CUDADevice(info, stats, background); } void device_cuda_info(vector& devices) { CUresult result; int count = 0; result = cuInit(0); if(result != CUDA_SUCCESS) { if(result != CUDA_ERROR_NO_DEVICE) fprintf(stderr, "CUDA cuInit: %s\n", CUDADevice::cuda_error_string(result)); return; } result = cuDeviceGetCount(&count); if(result != CUDA_SUCCESS) { fprintf(stderr, "CUDA cuDeviceGetCount: %s\n", CUDADevice::cuda_error_string(result)); return; } vector display_devices; for(int num = 0; num < count; num++) { char name[256]; int attr; if(cuDeviceGetName(name, 256, num) != CUDA_SUCCESS) continue; DeviceInfo info; info.type = DEVICE_CUDA; info.description = string(name); info.id = string_printf("CUDA_%d", num); info.num = num; int major, minor; cuDeviceComputeCapability(&major, &minor, num); info.advanced_shading = (major >= 2); info.pack_images = false; /* if device has a kernel timeout, assume it is used for display */ if(cuDeviceGetAttribute(&attr, CU_DEVICE_ATTRIBUTE_KERNEL_EXEC_TIMEOUT, num) == CUDA_SUCCESS && attr == 1) { info.display_device = true; display_devices.push_back(info); } else devices.push_back(info); } if(!display_devices.empty()) devices.insert(devices.end(), display_devices.begin(), display_devices.end()); } CCL_NAMESPACE_END